Query indexing and velocity constrained indexing: Scalable techniques for continuous queries on moving objects

被引:173
作者
Prabhakar, S [1 ]
Xia, YN [1 ]
Kalashnikov, DV [1 ]
Aref, WG [1 ]
Hambrusch, SE [1 ]
机构
[1] Purdue Univ, Dept Comp Sci, W Lafayette, IN 47907 USA
基金
美国国家科学基金会;
关键词
moving objects; spatio-temporal indexing; continuous queries; query indexing;
D O I
10.1109/TC.2002.1039840
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Moving object environments are characterized by large numbers of moving objects and numerous concurrent continuous queries over these objects. Efficient evaluation of these queries in response to the movement of the objects is critical for supporting acceptable response times. In such environments, the traditional approach of building an index on the objects (data) suffers from the need for frequent updates and thereby results in poor performance. In fact, a brute force, no-index strategy yields better performance in many cases. Neither the traditional approach nor the brute force strategy achieve reasonable query processing times. This paper develops novel techniques for the efficient and scalable evaluation of multiple continuous queries on moving objects. Our solution leverages two complimentary techniques: Query Indexing and Velocity Constrained Indexing (VCI). Query Indexing relies on 1) incremental evaluation, 2) reversing the role of queries and data, and 3) exploiting the relative locations of objects and queries. VCI takes advantage of the maximum possible speed of objects in order to delay the expensive operation of updating an index to reflect the movement of objects. In contrast to an earlier technique [29] that requires exact knowledge about the movement of the objects, VCI does not rely on such information. While Query Indexing outperforms VCI, it does not efficiently handle the arrival of new queries. Velocity constrained indexing, on the other hand, is unaffected by changes in queries. We demonstrate that a combination of Query Indexing and Velocity Constrained Indexing enables the scalable execution of insertion and deletion of queries in addition to processing ongoing queries. We also develop several optimizations and present a detailed experimental evaluation of our techniques. The experimental results show that the proposed schemes outperform the traditional approaches by almost two orders of magnitude.
引用
收藏
页码:1124 / 1140
页数:17
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